Twitter is many things to politicians and political junkies: a newsfeed, a megaphone—even the place where a promising promising career can quickly devolve into chaos. The 200 million tweets sent each day are also a data trove that researchers are mining for insights into forces like the influence of campaign cash, party affiliation trends, and, in a new study, the reasons people tweet about politics in the first place.

Computer scientist Saif Mohammad and his team at Canada’s National Research Council started with a million tweets related to America’s 2012 election, which they found using hashtags like #gop, #Obama and #RomneyRyan2012. With the help of crowdsourcing, they then classified a sample of about 2,000 tweets, with multiple readers assigning one of 11 purposes to each message. The most popular inspirations the annotators identified were “to support” (26%), “to ridicule” (15%) and “to provide information without any emotional content” (13%).

Mostly, they found negativity–criticism, venting, charges of hypocrisy. “The number of messages posted to oppose someone or something were almost twice the number of messages posted to offer support,” Mohammad writes. The researchers also waded into the popular, developing world of sentiment analysis, asking different annotators to assign emotions to the same tweets. The team then used features like emotion-related keywords to build a computer model that would automatically detect why a tweet was sent. The model identified the same purpose as the humans had in nearly half its guesses.

Any political strategist would love to know the Twittersphere’s aggregated sentiments in an instant. But the existence of a program that can systematically understand the meaning of tweets–with all their irony and nuance–is a long way off. Still, Mohammed’s results are a step in that direction and his paper looks ahead to that day, explaining how such research could be used to detect the electorate’s mood, or assess voter opinion about key policies and issues.

Other researchers are zeroing in on clues to whether a tweeter is a Republican or a Democrat. In a 2011 study published by Yahoo Labs, researchers gathered keywords more likely to be used by liberals or conservatives. Democrats, for instance, are more apt to tweet terms like rights, justice and reform. Republicans prefer constitution, economy and, of course, tea.

In July, computer scientists at Carnegie Mellon University published a study analyzing tweets from members of Congress. Their aim was to find a connection between what politicians tweeted about and where they got their campaign contributions. And they did. “You can actually guess [at the funding] that somebody’s getting based on the words they use,” says Noah Smith, one of the authors. “A congressman who uses the hashtag #sopa and talks about the Internet, he’s more likely to be funded by computing companies and groups.”

Smith has also worked on papers that use language analysis to mirror Gallup’s economic confidence poll and presidential approval ratings. He has even pursued the holy grail of political Twitter research: predicting the outcomes of elections. Though some academics have trumpeted positive results, most researchers are skeptical on this point. “I Wanted to Predict Elections with Twitter and all I got was this Lousy Paper,” was the title of one Spanish researcher’s 2012 paper, which noted that Twitter users are not a random sample and that academics often fail to account for factors like an incumbent’s statistical advantage.

Researchers will continue chasing the dream of forecasting election results through social media. In the meantime, they’ll have to settle for more modest findings–like that political wonks are more likely to tweet in anger than in praise.